Guides
By AnyCap Team
Practical guides
for agent teams and creators.
These guides cover setup, context design, tool integration, and working patterns for teams and creators using agents with AnyCap.
What these guides are for
The guides section is where implementation intent turns into repeatable operator knowledge. It covers installation, context design, capability routing, and the patterns that help teams move from one-off experiments to stable agent workflows.
In practice, these pages work best when the user already knows the capability gap and needs an execution path, not just a feature description. That is why the guides emphasize decisions, setup order, and workflow fit rather than only product messaging.
MCP vs Skills
Understand when you need the protocol layer, the instruction layer, or both for an agent workflow.
Human-in-the-Loop AI Agents
Design explicit approval, correction, and escalation checkpoints that return structured human feedback to an agent workflow.
Context Engineering for Agents
Structure prompts, files, and working context so agents stay grounded and useful.
Agent Skills for Developer Tools
Use reusable skills to keep agent workflows consistent across projects.
What Is Agent Harness?
Understand the execution layer that turns tool access into dependable agent behavior.
How to Add Image Generation to AI Agent
Add image-generation workflows to an AI agent without stitching together separate provider SDKs by hand.
How to Add Video Generation to AI Agent
Add video-generation workflows to an AI agent through one capability layer instead of one-off media API wiring.
How to Add Vision to AI Agent
Add image-reading and visual analysis workflows to an AI agent through a stable capability surface.
Claude Opus 4.7 Image and Video Workflow
Run a full image and video production workflow inside Claude Opus 4.7 with AnyCap as the capability layer.
What you will find here
- Installation and onboarding guides for AnyCap and supported agent environments.
- Architecture explainers that clarify how skills, MCP, context engineering, and runtime layers fit together.
- Workflow-oriented pages that show how to add generation and vision capabilities to real agents step by step.